interactive plot description

app.py

@@ -13,17 +13,21 @@ def plot_interactive(snr_list, alpha, y_axis, x_axis, colorbar_var):
     import io
     import PIL.Image
     buf = io.BytesIO()
-    fig.savefig(buf, format='png')
+    fig.savefig(buf, format='png', dpi=300)
     buf.seek(0)
     img = PIL.Image.open(buf)
     return img
 
 with gr.Blocks() as demo:
     gr.Markdown("""
-        ## EMRI Mass vs Distance/Redshift Interactive Plot
-
-        This visualization shows the results of the search pipeline for detecting Extreme Mass Ratio Inspirals (EMRIs) in simulated LISA data presented in [Ab uno disce omnes: Single-harmonic search for extreme mass-ratio inspirals](https://arxiv.org/abs/2510.20891).
-
+        ## EMRI Search Mass vs Distance/Redshift Interactive Plot
+
+        This visualization shows the sources detected by the search pipeline presented in [Ab uno disce omnes: Single-harmonic search for extreme mass-ratio inspirals](https://arxiv.org/abs/2510.20891).
+        On the x-axis, you can choose to plot either the primary or secondary mass of the detected sources. 
+        On the y-axis, you can choose to plot either the redshift or luminosity distance. 
+        The color of the points corresponds to a variable of your choice (initial eccentricity, final eccentricity, primary mass, or secondary mass).
+        Since the injection was performed in the detector frame, the masses are plotted in the source frame by dividing by (1+z).
+        
         For a quick, simplified EMRI search, open and run [QuickStartEMRIsearch.ipynb](examples/QuickStartEMRIsearch.ipynb). The notebook walks through the pipeline and produces example outputs, including:
 
         If you use this code, please cite the [paper](https://ui.adsabs.harvard.edu/abs/2026PhRvD.113b4061S)
@@ -36,8 +40,8 @@ with gr.Blocks() as demo:
         y_axis_input = gr.Radio(["Redshift", "Luminosity Distance"], label="Y Axis", value="Redshift")
         x_axis_input = gr.Radio(["Primary Mass", "Secondary Mass"], label="X Axis", value="Primary Mass")
 
-    colorbar_input = gr.Dropdown(["Final eccentricity $e_f$", "Initial eccentricity $e_0$", 
-                                  "Primary mass $m_1$", "Secondary mass $m_2$"], label="Colorbar Variable", value="ef")
+    colorbar_input = gr.Dropdown([r"Final eccentricity", r"Initial eccentricity", 
+                                  r"Primary mass", r"Secondary mass"], label="Colorbar Variable", value=r"Final eccentricity")
     plot_btn = gr.Button("Click here to plot")
     plot_output = gr.Image(type="pil")
 

scatter_plot_snr.py

@@ -80,27 +80,14 @@ def plot_mass_vs_distance_or_redshift(
     filtered_ef = ef_values[det_mask]
     filtered_e0 = e0_values[det_mask]
 
-    # Choose colorbar variable
-    if colorbar_var == "ef":
-        color_data = filtered_ef
-        color_label = 'Final Eccentricity ($e_f$)'
-        cmap = 'plasma'
-    elif colorbar_var == "e0":
-        color_data = filtered_e0
-        color_label = 'Initial Eccentricity ($e_0$)'
-        cmap = 'cividis'
-    elif colorbar_var == "m1":
-        color_data = filtered_m1
-        color_label = 'Primary Mass [M$_\odot$]'
-        cmap = 'viridis'
-    elif colorbar_var == "m2":
-        color_data = filtered_m2
-        color_label = 'Secondary Mass [M$_\odot$]'
-        cmap = 'viridis'
-    else:
-        color_data = filtered_ef
-        color_label = 'Final Eccentricity ($e_f$)'
-        cmap = 'plasma'
+    # Map app.py dropdown input to variable
+    colorbar_map = {
+        r"Final eccentricity": (filtered_ef, 'Final Eccentricity $e_f$', 'plasma'),
+        r"Initial eccentricity": (filtered_e0, 'Initial Eccentricity $e_0$', 'cividis'),
+        r"Primary mass": (filtered_m1, 'Primary Mass [M$_\odot$]', 'viridis'),
+        r"Secondary mass": (filtered_m2, 'Secondary Mass [M$_\odot$]', 'viridis'),
+    }
+    color_data, color_label, cmap = colorbar_map.get(colorbar_var, (filtered_ef, 'Final Eccentricity ($e_f$)', 'plasma'))
 
     fig, ax = plt.subplots(figsize=(7, 5))
     if x_axis == "Primary Mass":